Paper Title :Enhancing Conversational Artificial Intelligence with Multimodal Retrieval Augmented Generation
Author :Sanjay Bhatt, Srushti Gajbhiye, Praveen Thenraj Gunasekaran, Selvakuberan Karuppasamy, Anshuman A. Mahapatra
Article Citation :Sanjay Bhatt ,Srushti Gajbhiye ,Praveen Thenraj Gunasekaran ,Selvakuberan Karuppasamy ,Anshuman A. Mahapatra ,
(2024 ) " Enhancing Conversational Artificial Intelligence with Multimodal Retrieval Augmented Generation " ,
International Journal of Advance Computational Engineering and Networking (IJACEN) ,
pp. 25-30,
Volume-12,Issue-9
Abstract : Recently, retrieval-augmented generation (RAG) based solutions have improved language generation by
leveraging an external nonparametric index, showing impressive performance despite constrained model sizes. However,
these models are limited to retrieving only textual knowledge. Multimodal RAG (MuRAG) was introduced to address these
limitations of RAG, which leverages image data along with text to utilize the full power of retrieval models. This paper
proposes a multimodal retrieval-augmented framework combining Simple RAG and MuRAG to enhance chatbot
experiences by utilizing domain-specific repositories with both text and image data. After explaining Simple RAG and
reviewing existing RAG and MuRAG research, a case study is presented where a company struggles to develop an efficient
Multimodal RAG framework for handling image and text data. The proposed comprehensive framework uses the latest
libraries and models, uniquely leveraging image data as a knowledge source to improve LLM-generated responses.
Recommendations are provided to enhance performance, efficiency, and reliability, ensuring accurate, contextually
appropriate, and standards-aligned responses.
Keywords - Artificial intelligence (AI), Large Language Model (LLM), Retrieval Augmented Generation (RAG),
Multimodal Model, Generative Pre-Trained Transformers (GPT), LangChain, Facebook AI Similarity Search (FAISS)
Type : Research paper
Published : Volume-12,Issue-9
DOIONLINE NO - IJACEN-IRAJ-DOIONLINE-21243
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Copyright: © Institute of Research and Journals
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Published on 2025-01-08 |
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